fak
anthony-chaudhary/fak/llms-full.txt
agent kernel: full documentation corpus > This file inlines the full text of every document the curated `llms.txt` links to, for one-fetch ingestion by LLMs and answer engines. Generated
How real projects summarise themselves for language models.
anthony-chaudhary/fak/llms-full.txt
agent kernel: full documentation corpus > This file inlines the full text of every document the curated `llms.txt` links to, for one-fetch ingestion by LLMs and answer engines. Generated
anthony-chaudhary/fak/llms.txt
documentation map for agents `fak` is an agent runtime: the operator-controlled boundary for cache and context, model routing, tool authority, memory, observability, and native inference. Its technical architecture
ChaoYue0307/awesome-graph-engineering/docs/llms.txt
README resource tables, and website atlas are generated views. Repository-created metadata, schema, summaries, documentation, code, and visual assets are dedicated to the public domain under CC0 1.0 Universal; linked
drafthq/draft/web/llms-full.txt
Operations & lifecycle router (deploy-checklist, incident-response, standup, status, revert) - **`/draft:docs`** — Authoring router (documentation) - **`/draft:discover`** — Investigation & quality router (debug, bughunt, quick/deep-review, coverage, testing-strategy, learn, tour, impact, assist
drafthq/draft/web/llms.txt
review, now with graph-backed structural checks ## Key Concepts - **Context-Driven Development (CDD):** Structured documents constrain and guide AI behavior - **Tracks:** Isolated units of work with spec.md, plan.md, metadata.json
hoangsonww/AI-News-Briefing/llms.txt
llms.txt](https://llmstxt.org) convention so AI assistants and language models can find authoritative project documentation directly. Markdown links point at the canonical source for each topic. ## Core documentation - [README
HorizunGroup/horizun-revit-mcp/llms.txt
final connection steps in docs/CLIENTS.md. For Claude Desktop, Setup delivers a .mcpb to Documents\Horizun-Revit-MCP; the person installs it inside Claude Desktop and restarts the app. The extension
mindcloud-inc/universal-api-reference/llms.txt
MindCloud App Reference > Reference documentation for 3219 app APIs (76310 actions), all callable through MindCloud's Universal API: one REST interface with uniform authentication, pagination (limit/offset), RSQL filtering (where
rhein1/agoragentic-integrations/llms-full.txt
hosted runtimes, spend, settle x402, publish listings, mutate trust, or require native bindings. - **AnyDoc Document Evidence Adapter**: `examples/anydoc-document-evidence/` is an experimental source-only Node >=20 package for process-isolated local
rhein1/agoragentic-integrations/llms.txt
python rust-framework/python_call_rust_agent.py` (client examples only; no hosted provisioning or spend) - AnyDoc Document Evidence Adapter: `cd examples/anydoc-document-evidence && npm ci` (experimental source-only Node >=20 package; local process-isolated parsing
SiyaoZheng/GEZHI/llms.txt
this only when improving reusable examples, checks, or docs in this repository. ## Core Documentation - [README](README.md): Product overview and one-prompt quick start. - [Installation](docs/installation.md): Install details and local setup
agentskillexchange/skills/llms.txt
Security Reviewed description: Use anything2explainer as an agent workflow for turning a topic or document into a sourced Remotion explainer video with narration, subtitles, checkpoints, and QC. url: https://agentskillexchange.com
bsmi021/mcp-file-context-server/docs/llms-full.txt
# Example Clients Source: https://modelcontextprotocol.io/clients A list of applications that support MCP integrations
microsoft-foundry/forgebook/site/public/llms.txt
github.com/microsoft-foundry/forgebook): Notebook source, registry metadata, site code, and contribution guidance. - [Microsoft Foundry documentation](https://learn.microsoft.com/azure/foundry): Official Microsoft Foundry documentation
Servosity/msp-skills/docs/llms-full.txt
# MSP Skills - full corpus > Free MCP servers and Skills connecting MSP tools to the
Servosity/msp-skills/docs/llms.txt
Page: https://msp-skills.compoundingteams.com/skills/hubspot/ Install: bash <(curl -fsSL https://raw.githubusercontent.com/servosity/msp-skills/main/skills/hubspot/install.sh) - Hudu (Documentation) - ask "Which clients have the worst documentation completeness?" - Audit Hudu documentation hygiene, find stale passwords and expiring
simonlin1212/FactReach/llms.txt
Step-by-step setup instructions for AI agents - [README (中文)](https://github.com/simonlin1212/FactReach/blob/main/README.md): Full documentation in Chinese - [README (English)](https://github.com/simonlin1212/FactReach/blob/main/README_en.md): Full documentation in English ## Core Commands - [CLI Usage
booklib-ai/booklib/llms-full.txt
spiders, items, pipelines, rules), Storing Data (Ch 6: CSV, MySQL, files, email), Reading Documents (Ch 7: PDF, Word, encoding), Cleaning Data (Ch 8: normalization, OpenRefine), NLP (Ch 9: n-grams
lineai-intelligence/lineai-mcp-server/context/llms-full.txt
LLMs | | | Server-initiated LLM completions | | | Filesystem boundary definitions | | | User information requests | | | [Client ID Metadata Document](specification/latest/basic/authorization#client-id-metadata-documents) support | | | [Dynamic Client Registration](specification/latest/basic/authorization#dynamic-client-registration) support | | | [OAuth
luuuc/sense/docs/llms-full.txt
Sense — Full Documentation > Local MCP server giving AI coding agents structural understanding of a codebase (symbols, relationships, conventions) without reading dozens of files. One binary, one local index, four tools
A markdown file at a website's root that gives language models a short guide to the site and links to the pages worth reading.
The same idea with the content included, so an agent can read the documentation in one request.
Agents and tools that fetch documentation on someone's behalf. It's a proposal, not a standard, and support varies.
Start with a one-line summary, then sections of links with a sentence each. The examples here show what real projects do.